淡江大學機構典藏:Item 987654321/64873
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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/64873


    Title: A Reinterpretation of Empirical Mode Decomposition using Spectral Analysis Signal Reconstruction Method: Applications for Price Discovery of Futures and Spot Prices on WTI
    Authors: 張紘炬(Horng Jinh Chang);Pai, Ming-chu;Goo, Y. Jia;Hsu, Shih-chang
    Contributors: 淡江大學經營決策學系
    Keywords: Empirical Mode Decomposition;Price Discovery;Cumulative Intrinsic Mode Functions
    Date: 2011-03-01
    Issue Date: 2011-10-20 16:06:37 (UTC+8)
    Abstract: There are many studies on the correlation between spot prices and futures, most of them use stationary data for analysis. As a result, most research on the correlation between spot prices and futures use the rate of return for empirical analysis. In fact, stationary transformation often confuses the original nature of the data. Therefore, this study selects the West Texas Crude oil spot and futures prices as empirical objects, and applies [19] empirical mode decomposition (EMD). The EMD method decomposes the time sequence into several intrinsic mode functions (IMFs) and a monotonic function. Spectral analysis reveals IMF cycles, and aggregates IMFs into three component sequences based on the classification of practice and theory: short-term, medium-term, and long-term. This approach produces cumulative intrinsic mode functions (CIMFs). This study discusses cross correlation using the cross-correlation function and VAR. Results show that a short-term change of futures leads to price discovery for a short-term change in spot prices. This result is consistent with previous studies on price discovery using the rate of return. Unlike previous research, this study shows that a medium-term change of futures also leads to price discovery for a medium-term change in spot prices.
    Relation: Advanced Institute of Convergence IT,vol.6, number 3,March 2011, P.132-145
    Appears in Collections:[Department of Management Sciences] Journal Article

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